Central auditory neurons have composite receptive fields

High-level neurons processing complex, behaviorally relevant signals are sensitive to conjunctions of features. Characterizing the receptive fields of such neurons is difficult with standard statistical tools, however, and the principles governing their organization remain poorly understood. Here, we demonstrate multiple distinct receptive-field features in individual high-level auditory neurons in a songbird, European starling, in response to natural vocal signals (songs). We then show that receptive fields with similar characteristics can be reproduced by an unsupervised neural network trained to represent starling songs with a single learning rule that enforces sparseness and divisive normalization. We conclude that central auditory neurons have composite receptive fields that can arise through a combination of sparseness and normalization in neural circuits. Our results, along with descriptions of random, discontinuous receptive fields in the central olfactory neurons in mammals and insects, suggest general principles of neural computation across sensory systems and animal classes

Comparison and Mapping Facilitate Relation Discovery and Predication

Relational concepts play a central role in human perception and cognition, but little is known about how they are acquired. For example, how do we come to understand that physical force is a higher-order multiplicative relation between mass and acceleration, or that two circles are the same-shape in the same way that two squares are? A recent model of relational learning, DORA (Discovery of Relations by Analogy; Doumas, Hummel & Sandhofer, 2008), predicts that comparison and analogical mapping play a central role in the discovery and predication of novel higher-order relations. We report two experiments testing and confirming this prediction

Students’ analogical reasoning in novel situations: theory-like misconceptions or p-prims?

Over the past 50 years there has been much research in the area of students' misconceptions. Whilst this research has been useful in helping to inform the design of instructional approaches and curriculum development it has not provided much insight into how students reason when presented with a novel situation and, in particular, the knowledge they draw upon in an attempt to make predictions about that novel situation. This article reports on a study of Greek students, aged from 10 to 17 years old, who were asked to make predictions in novel situations and to then provide, without being told whether their predictions were correct or incorrect, explanations about their predictions. Indeed, their explanations in such novel situations have the potential to reveal how their ideas, as articulated as predictions, are formed as well as the sources they draw upon to make those predictions. We also consider in this article the extent to which student ideas can be seen either as theory-like misconceptions or, alternatively, as situated acts of construction involving the activation of fragmented pieces of knowledge referred to as phenomenological primitives (p-prims). Our findings suggest that in most cases students' reasoning in novel situations can be better understood in terms of their use of p-prims and that teaching might be made more effective if teachers were more aware of the p-prims that students were likely to be using when presented with new situations in physics

ACUOS: A System for Modular ACU Generalization with Subtyping and Inheritance

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-11558-0_40Computing generalizers is relevant in a wide spectrum of automated reasoning areas where analogical reasoning and inductive inference are needed. The ACUOS system computes a complete and minimal set of semantic generalizers (also called “anti-unifiers”) of two structures in a typed language modulo a set of equational axioms. By supporting types and any (modular) combination of associativity (A), commutativity (C), and unity (U) algebraic axioms for function symbols, ACUOS allows reasoning about typed data structures, e.g. lists, trees, and (multi-)sets, and typical hierarchical/structural relations such as is a and part of. This paper discusses the modular ACU generalization tool ACUOS and illustrates its use in a classical artificial intelligence problem.This work has been partially supported by the EU (FEDER) and the Spanish MINECO under grants TIN 2010-21062-C02-02 and TIN 2013-45732-C4-1-P, by Generalitat Valenciana PROMETEO2011/052, and by NSF Grant CNS 13-10109. J. Espert has also been supported by the Spanish FPU grant FPU12/06223.Alpuente Frasnedo, M.; Escobar Román, S.; Espert Real, J.; Meseguer, J. (2014). ACUOS: A System for Modular ACU Generalization with Subtyping and Inheritance. En Logics in Artificial Intelligence. Springer. 573-581. https://doi.org/10.1007/978-3-319-11558-0_40S573581Alpuente, M., Escobar, S., Espert, J., Meseguer, J.: A Modular Order-sorted Equational Generalization Algorithm. Information and Computation 235, 98–136 (2014)Alpuente, M., Escobar, S., Meseguer, J., Ojeda, P.: A Modular Equational Generalization Algorithm. In: Hanus, M. (ed.) LOPSTR 2008. LNCS, vol. 5438, pp. 24–39. Springer, Heidelberg (2009)Alpuente, M., Escobar, S., Meseguer, J., Ojeda, P.: Order–Sorted Generalization. ENTCS 246, 27–38 (2009)Alpuente, M., Espert, J., Escobar, S., Meseguer, J.: ACUOS: A System for Modular ACU Generalization with Subtyping and Inheritance. Tech. rep., DSIC-UPV (2013), http://www.dsic.upv.es/users/elp/papers.htmlArmengol, E.: Usages of Generalization in Case-Based Reasoning. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 31–45. Springer, Heidelberg (2007)Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C. (eds.): All About Maude - A High-Performance Logical Framework. LNCS, vol. 4350. Springer, Heidelberg (2007)Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C.L.: Reflection, metalevel computation, and strategies. In: All About Maude [6], pp. 419–458Gentner, D.: Structure-Mapping: A Theoretical Framework for Analogy*. Cognitive Science 7(2), 155–170 (1983)Krumnack, U., Schwering, A., Gust, H., Kühnberger, K.-U.: Restricted higher order anti unification for analogy making. In: Orgun, M.A., Thornton, J. (eds.) AI 2007. LNCS (LNAI), vol. 4830, pp. 273–282. Springer, Heidelberg (2007)Kutsia, T., Levy, J., Villaret, M.: Anti-Unification for Unranked Terms and Hedges. Journal of Automated Reasoning 520, 155–190 (2014)Meseguer, J.: Conditioned rewriting logic as a united model of concurrency. Theor. Comput. Sci. 96(1), 73–155 (1992)Muggleton, S.: Inductive Logic Programming: Issues, Results and the Challenge of Learning Language in Logic. Artif. Intell. 114(1-2), 283–296 (1999)Ontañón, S., Plaza, E.: Similarity measures over refinement graphs. Machine Learning 87(1), 57–92 (2012)Plotkin, G.: A note on inductive generalization. In: Machine Intelligence, vol. 5, pp. 153–163. Edinburgh University Press (1970)Pottier, L.: Generalisation de termes en theorie equationelle: Cas associatif-commutatif. Tech. Rep. INRIA 1056, Norwegian Computing Center (1989)Schmid, U., Hofmann, M., Bader, F., Häberle, T., Schneider, T.: Incident Mining using Structural Prototypes. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds.) IEA/AIE 2010, Part II. LNCS, vol. 6097, pp. 327–336. Springer, Heidelberg (2010

Analogical cognition: an insight into word meaning

Analogical cognition, extensively researched by Dedre Gentner and her colleagues over the past thirty five years, has been described as the core of human cognition, and it characterizes our use of many words. This research provides significant insight into the nature of word meaning, but it has been ignored by linguists and philosophers of language. I discuss some of the implications of the research for our account of word meaning. In particular, I argue that the research points to, and helps account for, a key explanatory role that linguistic meaning must play. The research also shows how words contribute to thought as opposed to merely being a means of conveying thought

Using conceptual metaphor and functional grammar to explore how language used in physics affects student learning

This paper introduces a theory about the role of language in learning physics. The theory is developed in the context of physics students' and physicists' talking and writing about the subject of quantum mechanics. We found that physicists' language encodes different varieties of analogical models through the use of grammar and conceptual metaphor. We hypothesize that students categorize concepts into ontological categories based on the grammatical structure of physicists' language. We also hypothesize that students over-extend and misapply conceptual metaphors in physicists' speech and writing. Using our theory, we will show how, in some cases, we can explain student difficulties in quantum mechanics as difficulties with language.Comment: Accepted for publication in Phys. Rev. ST:PE

ISML: an interface specification meta-language

In this paper we present an abstract metaphor model situated within a model-based user interface framework. The inclusion of metaphors in graphical user interfaces is a well established, but mostly craft-based strategy to design. A substantial body of notations and tools can be found within the model-based user interface design literature, however an explicit treatment of metaphor and its mappings to other design views has yet to be addressed. We introduce the Interface Specification Meta-Language (ISML) framework and demonstrate its use in comparing the semantic and syntactic features of an interactive system. Challenges facing this research are outlined and further work proposed

Association between exposure to environmental tobacco smoke and biomarkers of oxidative stress among patients hospitalised with acute myocardial infarction

Objective To determine whether exposure to environmental tobacco smoke was associated with oxidative stress among patients hospitalised for acute myocardial infarction.<p></p> Design An existing cohort study of 1,261 patients hospitalised for acute myocardial infarction.<p></p> Setting Nine acute hospitals in Scotland.<p></p> Participants Sixty never smokers who had been exposed to environmental tobacco smoke (admission serum cotinine ≥3.0 ng/mL) were compared with 60 never smokers who had not (admission serum cotinine ≤0.1 ng/mL).<p></p> Intervention None.<p></p> Main outcome measures Three biomarkers of oxidative stress (protein carbonyl, malondialdehyde (MDA) and oxidised low-density lipoprotein (ox-LDL)) were measured on admission blood samples and adjusted for potential confounders.<p></p> Results After adjusting for baseline differences in age, sex and socioeconomic status, exposure to environmental tobacco smoke was associated with serum concentrations of both protein carbonyl (beta coefficient 7.96, 95% CI 0.76, 15.17, p = 0.031) and MDA (beta coefficient 10.57, 95% CI 4.32, 16.81, p = 0.001) but not ox-LDL (beta coefficient 2.14, 95% CI −8.94, 13.21, p = 0.703).<p></p> Conclusions Exposure to environmental tobacco smoke was associated with increased oxidative stress. Further studies are requires to explore the role of oxidative stress in the association between environmental tobacco smoke and myocardial infarction.<p></p&gt